HR AI Skill

Recruitment Analytics

Analyze hiring funnel metrics, source effectiveness, time-to-hire, cost-per-hire, quality-of-hire, and diversity hiring data. Use when generating recruitment dashboards, identifying bottlenecks, optimizing sourcing channels, tracking recruiter performance, or presenting hiring metrics to leadership. Supports weekly, monthly, and quarterly reporting with trend analysis and AI-powered recommendations. Triggers on phrases like "hiring metrics", "recruitment dashboard", "time to hire", "cost per hire", "source of hire", "funnel analysis", "hiring report", "recruiting KPIs".

Recruitment Analytics

Measure and optimize the hiring process with data-driven insights.

Workflow

Pull data from ATS, HRIS, and sourcing tools for the reporting period.
Calculate core metrics: time-to-fill, time-to-hire, cost-per-hire, offer acceptance rate, quality-of-hire.
Analyze funnel conversion rates at each stage: applied → screened → interviewed → offered → hired.
Identify bottlenecks: stages with lowest conversion or longest average duration.
Evaluate source effectiveness: which channels produce the best candidates at the lowest cost.
Assess diversity metrics: applicant pool diversity vs. hired diversity at each stage.
Generate dashboard and executive summary.
Surface actionable recommendations based on trends and benchmarks.

Core Metrics Definitions

| Metric | Formula | Target | Benchmark (Tech) | |--------|---------|--------|-----------------| | Time-to-Fill | Days from requisition approval to offer acceptance | < 45 days | 36–52 days | | Time-to-Hire | Days from application to offer acceptance | < 30 days | 25–35 days | | Cost-per-Hire | (Internal costs + External costs) ÷ Total hires | Varies by role | $4,000–$9,000 | | Offer Acceptance Rate | Offers accepted ÷ Offers extended × 100 | > 85% | 80–90% | | Application-to-Offer Rate | Offers extended ÷ Applications received × 100 | 2–5% | 1–8% | | Quality-of-Hire | (Performance rating × 0.4) + (Retention × 0.3) + (Manager satisfaction × 0.3) | > 4.0/5.0 | 3.5–4.5 | | First-90-Day Attrition | New hires leaving within 90 days ÷ Total new hires × 100 | < 5% | 3–8% | | Source-of-Hire Effectiveness | Hires from source ÷ Cost from source | Maximize ratio | Varies |

Funnel Analysis

Stage Conversion Tracking

FUNNEL VIEW — Q1 2025
======================

Stage               Count    Conversion    Drop-off    Avg Duration
────────────────────────────────────────────────────────────────────
Applications         2,450    —            —           —
Resume Screen        890      36.3%        63.7%       2.1 days
Phone Screen         312      35.1%        64.9%       3.4 days
Technical Interview   145      46.5%       53.5%       5.2 days
Final Round           68      46.9%        53.1%       4.8 days
Offer Extended        42      61.8%        38.2%       2.1 days
Offer Accepted        35      83.3%        16.7%       5.2 days
Hired                 35      100%         —           —

Overall conversion: 1.43% (35 hired ÷ 2,450 applied)
Total time-to-hire: 22.8 days (median)

BOTTLENECK IDENTIFIED:
  → Resume screen: 63.7% drop-off is normal for volume roles
  → Phone screen: 64.9% drop-off — consider if screening criteria are too strict
  → Offer stage: 16.7% decline rate — investigate top decline reasons

Funnel Health Indicators

| Signal | Meaning | Action | |--------|---------|--------| | High application count, low screen rate | JD attracts wrong candidates | Rewrite JD, refine targeting | | Low application count | Role not visible or uncompetitive | Increase sourcing, review comp | | High interview-to-offer drop-off | Interview process too harsh or poorly calibrated | Review interviewer training, calibrate scoring | | Low offer acceptance rate | Comp uncompetitive or process too long | Benchmark comp, accelerate process | | High first-90-day attrition | Poor hiring quality or bad onboarding | Review screening rigor, audit onboarding |

Source Effectiveness Analysis

SOURCE EFFECTIVENESS — Q1 2025
==============================

Source            Applicants  Hires  Cost/Hire  Quality*  ROI Score
────────────────────────────────────────────────────────────────────
Employee Referral     312       8    $2,100     4.3/5    ★★★★★
LinkedIn              685       9    $4,800     3.8/5    ★★★★☆
Indeed                420       5    $3,200     3.5/5    ★★★☆☆
Company Career Site   390       6    $1,800     3.9/5    ★★★★☆
Direct Sourcing       180       4    $5,600     4.1/5    ★★★☆☆
Agency                45        2    $12,000    3.6/5    ★★☆☆☆
University           18         1    $3,500     4.0/5    ★★★☆☆
Diversity Boards      100       2    $2,800     3.7/5    ★★★☆☆

*Quality = avg performance rating of hires from source at 6-month review

RECOMMENDATION:
  → Increase employee referral incentive (highest ROI)
  → Reduce agency spend (lowest ROI, highest cost)
  → Maintain LinkedIn investment (volume + quality balance)
  → Test diversity board expansion (decent quality, room for scale)

Diversity Hiring Metrics

Track representation at each funnel stage:

DIVERSITY FUNNEL — Q1 2025
==========================

Stage             All    Women    Underrep.    LGBTQ+    Disability
────────────────────────────────────────────────────────────────────
Applications     2,450   42%      38%         8%        5%
Screened          890    40%      35%         7%        4%
Interviewed       312    38%      33%         6%        4%
Offered           42     36%      31%         5%        3%
Hired             35     37%      32%         5%        4%

WORKFORCE BASELINE (for comparison):
  Current workforce: Women 34%, Underrep. 28%, LGBTQ+ 6%, Disability 4%

ASSESSMENT:
  ✓ Hiring slightly above workforce baseline for women (+3%)
  ⚠ Underrepresented groups declining through funnel (-6% from apply to hire)
  ✓ LGBTQ+ and disability representation maintained
  → ACTION: Review screening rubric for implicit bias at phone screen stage

Recruiter Performance Metrics

RECRUITER LEADERBOARD — Q1 2025
================================

Recruiter      Hires  Time-to-Fill  Offer Accept  Quality     Revenue Impact
─────────────────────────────────────────────────────────────────────────────
Sarah M.        12     28 days      92%           4.2/5      $1.8M (sales hires)
James L.         9     35 days      85%           4.0/5      $920K (eng hires)
Priya K.        11     31 days      89%           4.1/5      $1.2M (mixed)
David R.         7     42 days      78%           3.7/5      $650K (eng hires)

NOTES:
  → Sarah: Top performer — consider expanding scope
  → David: Below target on time-to-fill and quality — recommend coaching session
  → All recruiters within acceptable range except David on quality metric

Reporting Cadence

| Report | Frequency | Audience | Format | |--------|-----------|----------|--------| | Weekly pipeline snapshot | Every Monday | Hiring managers, recruiters | Slack/Email summary | | Monthly hiring dashboard | 1st of month | HR leadership, department heads | Interactive dashboard | | Quarterly business review | End of quarter | Executive team, board | Presentation deck | | Annual hiring summary | End of year | Board, all-hands | Written report |

AI-Powered Recommendations

Surface these insights automatically:

Based on Q1 data, the system recommends:

1. ⚡ REDUCE TIME-TO-FILL FOR ENGINEERING ROLES
   Current: 38 days | Target: 30 days
   Action: Pre-screen candidates with automated skills assessments
   Impact estimate: -5 to -7 days per hire

2. 💰 OPTIMIZE SOURCING BUDGET
   Current agency spend: $24,000 (2 hires, $12K each)
   Action: Reallocate $15K to employee referral bonus program
   Impact estimate: 3-4 additional hires at $2.5K avg cost

3. 🎯 IMPROVE PHONE SCREEN CONVERSION
   Current drop-off: 64.9% at phone screen
   Action: Review screening rubric; calibrate recruiters on "pass" threshold
   Impact estimate: +10-15% conversion = 30-45 more candidates advancing

4. 📊 DIVERSITY INTERVENTION NEEDED
   Underrep. group drop-off: 38% → 32% through funnel
   Action: Implement blind resume screening for phone screen stage
   Impact estimate: +5-8% representation at offer stage

Integration Points

ATS (Greenhouse, Lever, Ashby): Pipeline data, stage timestamps
HRIS: Hire dates, performance data for quality-of-hire calculation
Sourcing platforms: Channel attribution, spend tracking
Payroll: Cost-per-hire internal cost calculation
BI tools (Tableau, Looker, Power BI): Dashboard visualization
Slack/Email: Automated report distribution

Edge Cases

Mass hiring periods: Adjust targets temporarily; track surge metrics separately
Hard-to-fill roles: Segment analytics by role difficulty; don't let outliers skew overall metrics
New company / no baseline: Use industry benchmarks as starting targets; build internal baseline over 6 months
Remote/global hiring: Segment metrics by region to account for market differences
Hiring freeze impact: Note freeze periods in trend analysis; exclude frozen weeks from time-to-fill calculations

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